Information processing in models for density-dependent emigration: A comparison

Density-dependent emigration has been recognized as a fitness enhancing strategy. Yet, especially in the modelling literature there is no consensus about how density-dependent emigration should quantitatively be incorporated into metapopulation models. In this paper we compare the performance of five different dispersal strategies (defined by the functional link between density and emigration probability). Four of these strategies are based on published functional relationships between local population density and emigration probability, one assumes density-independent dispersal. We use individual-based simulations of time-discrete metapopulation dynamics and conduct evolution experiments for a broad range of values for dispersal mortality and environmental stochasticity. For each set of these conditions we analyze the evolution of emigration rates in ‘monoculture experiments’ (with only one type of dispersal strategy used by all individuals in the metapopulation) as well as in selection experiments that allow a pair-wise comparison of the performance of each functional type. We find that a single-parameter ‘asymptotic threshold’ strategy - derived from the marginal value theorem - with a decelerating increase of emigration rate with increasing population density, out-competes any other strategy, i.e. density-independent emigration, a ‘linear threshold’ strategy and a flexible three-parameter strategy. Only when environmental conditions select for extremely high emigration probabilities (close to one), strategies may perform approximately equally. A simple threshold strategy derived for the case of continuous population growth performs even worse than the density-independent strategy. As the functional type of the dispersal function implemented in metapopulation models may severely affect predictions concerning the survival of populations, range expansion, or community changes we clearly recommend to carefully select adequate functions to model density-dependent dispersal.     

A model for behavioral regulation of metapopulation dynamics

Habitat fragmentation can decrease local population persistence by reducing connectivity, which is a function of dispersal of individuals among habitat fragments. Dispersal is often treated as diffusion in population models, even though for many species it is a result of a series of behavioral decisions. We developed a metapopulation model to explore the potential importance of dispersal behaviors in driving metapopulation dynamics. We incorporated types of behavior that affect dispersal—colonization inhibiting, colonization enhancing, extinction inhibiting, extinction enhancing, rescue enhancing, rescue inhibiting—into Levins’ (1969) metapopulation model and projected occupancy rates for a variety of parameter values. Examples from the literature of behaviors associated with each of these parameters are provided. Our model simplifies into previously published metapopulation models that incorporate only a single behavior, and we present a density-dependent rescue function that leads to multiple non-zero equilibria. We found a variety of behavioral effects on metapopulations. Rescue enhancement fills patches faster than does colonization enhancement or extinction inhibition, and declines in patch occupancy are moderate with extinction enhancement, but colonization inhibition causes metapopulation extinction. We also found that with colonization and extinction inhibitions, equilibrium patch occupancy is inversely related to patch turnover rate. With density-dependent rescue, persistence depends not only on the strength of the strong rescue effect, but also on having a sufficient initial fraction of patches occupied; the stronger the rescue effect, the lower this fraction can be. This study suggests that dispersal behavior can have strong influences on metapopulation dynamics. It confirms the importance of understanding the relationship between landscape structure and dispersal behavior in understanding population persistence.     

Habitat complexity modifies post-settlement mortality and recruitment dynamics of a marine fish

For species that have an open population structure, local population size may be strongly influenced by a combination of propagule supply and post-settlement survival. While it is widely recognized that supply of larvae (or recruits) is variable and that variable recruitment may affect the relative contribution of pre- and post-settlement factors, less effort has been made to quantify how variation in the strength of post-settlement mortality (particularly density-dependent mortality) will affect the importance of processes that determine population size. In this study, I examined the effects of habitat complexity on mortality of blue rockfish (Sebastes mystinus) within nearshore reefs off central California. I first tested whether variation in habitat complexity (measured as three-dimensional complexity of rocky substrate) affected the magnitude of both density-independent and density-dependent mortality. I then used limitation analysis to quantify how variation in habitat complexity alters the relative influence of recruitment, density-independent mortality, and density-dependent mortality in determining local population size. Increased habitat complexity was associated with a reduction in both density-independent and density-dependent mortality. At low levels of habitat complexity, limitation analysis revealed that mortality was strong and recruitment had relatively little influence on population size. However, as habitat complexity increased, recruitment became more important. At the highest levels of habitat complexity, limitation by recruitment was substantial, although density-dependent mortality was ultimately the largest constraint on population size. In high-complexity habitats, population dynamics may strongly reflect variation in recruitment even though fluctuations may be dampened by density-dependent mortality. By affecting both density-independent and density-dependent mortality, variation in habitat complexity may result in qualitative changes in the dynamics of populations. These findings suggest that the relative importance of pre- vs. post-settlement factors may be determined by quantifiable habitat features, rather than ambient recruitment level alone. Because the magnitude of recruitment fluctuations can affect species coexistence and the persistence of populations, habitat-driven changes in population dynamics may have important consequences for both community structure and population viability.     

Consistent scaling of persistence time in metapopulations

Recent theory and experimental work in metapopulations and metacommunities demonstrates that long-term persistence is maximized when the rate at which individuals disperse among patches within the system is intermediate; if too low, local extinctions are more frequent than recolonizations, increasing the chance of regional-scale extinctions, and if too high, dynamics exhibit region-wide synchrony, and local extinctions occur in near unison across the region. Although common, little is known about how the size and topology of the metapopulation (metacommunity) affect this bell-shaped relationship between dispersal rate and regional persistence time. Using a suite of mathematical models, we examined the effects of dispersal, patch number, and topology on the regional persistence time when local populations are subject to demographic stochasticity. We found that the form of the relationship between regional persistence time and the number of patches is consistent across all models studied; however, the form of the relationship is distinctly different among low, intermediate, and high dispersal rates. Under low and intermediate dispersal rates, regional persistence times increase logarithmically and exponentially (respectively) with increasing numbers of patches, whereas under high dispersal, the form of the relationship depends on local dynamics. Furthermore, we demonstrate that the forms of these relationships, which give rise to the bell-shaped relationship between dispersal rate and persistence time, are a product of recolonization and the region-wide synchronization (or lack thereof) of population dynamics. Identifying such metapopulation attributes that impact extinction risk is of utmost importance for managing and conserving the earth's evermore fragmented populations.     

Demographic stochasticity reduces the synchronizing effect of dispersal in predator-prey metapopulations

Dispersal may affect predator-prey metapopulations by rescuing local sink populations from extinction or by synchronizing population dynamics across the metapopulation, increasing the risk of regional extinction. Dispersal is likely influenced by demographic stochasticity, however, particularly because dispersal rates are often very low in metapopulations. Yet the effects of demographic stochasticity on predator-prey metapopulations are not well known. To that end, I constructed three models of a two-patch predator-prey system. The models constitute a hierarchy of complexity, allowing direct comparisons. Two models included demographic stochasticity (pure jump process [PJP] and stochastic differential equations [SDE]), and the third was deterministic (ordinary differential equations [ODE]). One stochastic model (PJP) treated population sizes as discrete, while the other (SDE) allowed population sizes to change continuously. Both stochastic models only produced synchronized predator-prey dynamics when dispersal was high for both trophic levels. Frequent dispersal by only predators or prey in the PJP and SDE spatially decoupled the trophic interaction, reducing synchrony of the non-dispersive species. Conversely, the ODE generated synchronized predator-prey dynamics across all dispersal rates, except when initial conditions produced anti-phase transients. These results indicate that demographic stochasticity strongly reduces the synchronizing effect of dispersal, which is ironic because demographic stochasticity is often invoked post hoc as a driver of extinctions in synchronized metapopulations.     

Minimum viable metapopulation size, extinction debt, and the conservation of a declining species.

A key question facing conservation biologists is whether declines in species' distributions are keeping pace with landscape change, or whether current distributions overestimate probabilities of future persistence. We use metapopulations of the marsh fritillary butterfly Euphydryas aurinia in the United Kingdom as a model system to test for extinction debt in a declining species. We derive parameters for a metapopulation model (incidence function model, IFM) using information from a 625-km2 landscape where habitat patch occupancy, colonization, and extinction rates for E. aurinia depend on patch connectivity, area, and quality. We then show that habitat networks in six extant metapopulations in 16-km2 squares were larger, had longer modeled persistence times (using IFM), and higher metapopulation capacity (lambdaM) than six extinct metapopulations. However, there was a > 99% chance that one or more of the six extant metapopulations would go extinct in 100 years in the absence of further habitat loss. For 11 out of 12 networks, minimum areas of habitat needed for 95% persistence of metapopulation simulations after 100 years ranged from 80 to 142 ha (approximately 5-9% of land area), depending on the spatial location of habitat. The area of habitat exceeded the estimated minimum viable metapopulation size (MVM) in only two of the six extant metapopulations, and even then by only 20%. The remaining four extant networks were expected to suffer extinction in 15-126 years. MVM was consistently estimated as approximately 5% of land area based on a sensitivity analysis of IFM parameters and was reduced only marginally (to approximately 4%) by modeling the potential impact of long-distance colonization over wider landscapes. The results suggest a widespread extinction debt among extant metapopulations of a declining species, necessitating conservation management or reserve designation even in apparent strongholds. For threatened species, metapopulation modeling is a potential means to identify landscapes near to extinction thresholds, to which conservation measures can be targeted for the best chance of success.     

Negative relationship between dispersal distance and demography in butterfly metapopulations

Little is known about the connection between demography and dispersal in metapopulations. The meta-analysis of the population time series of five butterfly species indicated that (meta)population dynamics are driven by density-dependent factors. Inter-specific comparison reveals a significant inverse relationship between population growth rate and the magnitude of dispersal distance. As the range of dispersal distances is constrained by the patch system, dispersing individuals moving too far away would (probably) get lost. This generates selective pressures on individuals with a high dispersal propensity, but favors individuals investing more in reproduction and results in a higher (meta)population growth rate. From a conservation perspective, individuals from (meta)populations and species sacrificing dispersal for the sake of reproductive performances are most vulnerable because of their higher sensitivity to stochastic events: the temporal variation of growth rate was much higher in the two metapopulations where dispersal was limited.     

Effects of Climate Change on Population Persistence of Desert-Dwelling Mountain Sheep in California

Abstract:  Metapopulations may be very sensitive to global climate change, particularly if temperature and precipitation change rapidly. We present an analysis of the role of climate and other factors in determining metapopulation structure based on presence and absence data. We compared existing and historical population distributions of desert bighorn sheep ( Ovis canadensis ) to determine whether regional climate patterns were correlated with local extinction. To examine all mountain ranges known to hold or to have held desert bighorn populations in California and score for variables describing climate, metapopulation dynamics, human impacts, and other environmental factors, we used a geographic information system (GIS) and paper maps. We used logistic regression and hierarchical partitioning to assess the relationship among these variables and the current status of each population (extinct or extant). Parameters related to climate—elevation, precipitation, and presence of dependable springs—were strongly correlated with population persistence in the twentieth century. Populations inhabiting lower, drier mountain ranges were more likely to go extinct. The presence of domestic sheep grazing allotments was negatively correlated with population persistence. We used conditional extinction probabilities generated by the logistic-regression model to rank native, naturally recolonized, and reintroduced populations by vulnerability to extinction under several climate-change scenarios. Thus risk of extinction in metapopulations can be evaluated for global-climate-change scenarios even when few demographic data are available.     

The role of habitat disturbance and recovery in metapopulation persistence

Classical metapopulation theory assumes a static landscape. However, empirical evidence indicates many metapopulations are driven by habitat succession and disturbance. We develop a stochastic metapopulation model, incorporating habitat disturbance and recovery, coupled with patch colonization and extinction, to investigate the effect of habitat dynamics on persistence. We discover that habitat dynamics play a fundamental role in metapopulation dynamics. The mean number of suitable habitat patches is not adequate for characterizing the dynamics of the metapopulation. For a fixed mean number of suitable patches, we discover that the details of how disturbance affects patches and how patches recover influences metapopulation dynamics in a fundamental way. Moreover, metapopulation persistence is dependent not only on the average lifetime of a patch, but also on the variance in patch lifetime and the synchrony in patch dynamics that results from disturbance. Finally, there is an interaction between the habitat and metapopulation dynamics, for instance declining metapopulations react differently to habitat dynamics than expanding metapopulations. We close, emphasizing the importance of using performance measures appropriate to stochastic systems when evaluating their behavior, such as the probability distribution of the state of the metapopulation, conditional on it being extant (i.e., the quasistationary distribution).     

The inflationary effects of environmental fluctuations ensure the persistence of sink metapopulations

Under current rates of environmental change many populations may be found in habitats of low quality and low conservation value, creating population sinks. We test recent theory that suggests, surprisingly, that stochastic environmental variability may enhance the long-term persistence of sink metapopulations. Using experimental populations of Paramecium aurelia we show that it is possible for a metapopulation comprised entirely of sink populations to persist for many generations in a random environment. In accordance with the theory, we show that positive temporal autocorrelation and low spatial correlation in the environment can ensure the long-term persistence and enhance the mean and maximum abundance of sink metapopulations. High levels of spatial correlation in the environment created strong population synchrony and limited the persistence time of the sink metapopulations. These results have important implications for the development of a theory underlying the synergistic effects of habitat fragmentation and environmental change on population persistence.     

Dispersal depression with habitat fragmentation in the bog fritillary butterfly

Habitat fragmentation is expected to impose strong selective pressures on dispersal rates. However, evolutionary responses of dispersal are not self-evident, since various selection pressures act in opposite directions. Here we disentangled the components of dispersal behavior in a metapopulation context using the Virtual Migration model, and we linked their variation to habitat fragmentation in the specialist butterfly Proclossiana eunomia. Our study provided a nearly unique opportunity to study how habitat fragmentation modifies dispersal at the landscape scale, as opposed to microlandscapes or simulation studies. Indeed, we studied the same species in four landscapes with various habitat fragmentation levels, in which large amounts of field data were collected and analyzed using similar methodologies. We showed the existence of quantitative variations in dispersal behavior correlated with increased fragmentation. Dispersal propensity from habitat patches (for a given patch size), and mortality during dispersal (for a given patch connectivity) were lower in more fragmented landscapes. We suggest that these were the consequences of two different evolutionary responses of dispersal behavior at the individual level: (1) when fragmentation increased, the reluctance of individuals to cross habitat patch boundaries also increased; (2) when individuals dispersed, they flew straighter in the matrix, which is the best strategy to improve dispersal success. Such evolutionary responses could generate complex nonlinear patterns of dispersal changes at the metapopulation level according to habitat fragmentation. Due to the small size and increased isolation of habitat patches in fragmented landscapes, overall emigration rate and mortality during dispersal remained high. As a consequence, successful dispersal at the metapopulation scale remained limited. Therefore, to what extent the selection of individuals with a lower dispersal propensity and a higher survival during dispersal is able to limit detrimental effects of habitat fragmentation on dispersal success is unknown, and any conclusion that metapopulations would compensate for them is flawed.     

Developing Metapopulation Connectivity Criteria from Genetic and Habitat Data to Recover the Endangered Mexican Wolf

Restoring connectivity between fragmented populations is an important tool for alleviating genetic threats to endangered species. Yet recovery plans typically lack quantitative criteria for ensuring such population connectivity. We demonstrate how models that integrate habitat, genetic, and demographic data can be used to develop connectivity criteria for the endangered Mexican wolf (Canis lupus baileyi), which is currently being restored to the wild from a captive population descended from 7 founders. We used population viability analysis that incorporated pedigree data to evaluate the relation between connectivity and persistence for a restored Mexican wolf metapopulation of 3 populations of equal size. Decreasing dispersal rates greatly increased extinction risk for small populations (<150–200), especially as dispersal rates dropped below 0.5 genetically effective migrants per generation. We compared observed migration rates in the Northern Rocky Mountains (NRM) wolf metapopulation to 2 habitat‐based effective distance metrics, least‐cost and resistance distance. We then used effective distance between potential primary core populations in a restored Mexican wolf metapopulation to evaluate potential dispersal rates. Although potential connectivity was lower in the Mexican wolf versus the NRM wolf metapopulation, a connectivity rate of >0.5 genetically effective migrants per generation may be achievable via natural dispersal under current landscape conditions. When sufficient data are available, these methods allow planners to move beyond general aspirational connectivity goals or rules of thumb to develop objective and measurable connectivity criteria that more effectively support species recovery. The shift from simple connectivity rules of thumb to species‐specific analyses parallels the previous shift from general minimum‐viable‐population thresholds to detailed viability modeling in endangered species recovery planning. Desarrollo de Criterios de Conectividad Metapoblacional a Partir de Datos Genéticos y de Hábitat para Recuperar al Lobo Mexicano en Peligro de Extinción     

Dispersal connectivity and reserve selection for marine conservation

Although larval dispersal is crucial for the persistence of most marine populations, dispersal connectivity between sites is rarely considered in designing marine protected area networks. In particular the role of structural characteristics (known as topology) for the network of larval dispersal routes in the conservation of metapopulations has not been addressed. To determine reserve site configurations that provide highest persistence values with respect to their connectivity characteristics, we model nine connectivity topological models derived from graph theory in a demographic metapopulation model. We identify reserve site configurations that provide the highest persistence values for each of the metapopulation connectivity models. Except for the minimally connected and fully connected populations, we observed two general ‘rules of thumb’ for optimising the mean life time for all topological models: firstly place the majority of reserves, so that they are neighbours of each other, on the sites where the number of connections between the populations is highest (hub), secondly when the reserves have occupied the majority of the vertices in the hub, then select another area of high connectivity and repeat. If there are no suitable hubs remaining then distribute the remaining reserves to isolated locations optimising contact with non-reserved sites.     

A Habitat-Based Metapopulation Model of the California Gnatcatcher

We present an analysis of the metapopulation dynamics of the federally threatened coastal California Gnatcatcher (Polioptila c. californica) for an approximately 850 km² region of Orange County, California. We developed and validated a habitat suitability model for this species using data on topography, vegetation, and locations of gnatcatcher pair observations. Using this habitat model, we calculated the spatial structure of the metapopulation, including size and location of habitat patches and the distances among them. We used data based on field studies to estimate parameters such as survival, fecundity, dispersal, and catastrophes, and combined these parameters with the spatial structure to build a stage-structured, stochastic, spatially-explicit metapopulation model. The model predicted a fast decline and high risk of population extinction with most combinations of parameters. Results were most sensitive to density-dependent effects, the probability of weather-related catastrophes, adult survival, and adult fecundity. Based on data used in the model, the greatest difference in results was given when the simulation's time horizon was only a few decades, suggesting that modeling based on longer or shorter time horizons may underestimate the effects of alternative management actions.     

Catastrophic Reproductive Failure, Terrestrial Survival, and Persistence of the Marbled Salamander

Abstract:  Wide variation in reproductive success is common among amphibians that breed in seasonal ponds, but persistence of adults can buffer against these fluctuations, particularly for long-lived species. We hypothesized that the frequent episodes of catastrophic failure of the marbled salamander ( Ambystoma opacum ) enhance the importance of high terrestrial survival. At Rainbow Bay in South Carolina reproductive success was poor (<1 metamorph/breeding female) in nearly half of the 22 years that the species bred. Complete failure occurred in 6 of 22 years. To study catastrophic failure, we adapted an age-structured, individual-based model with density-dependent growth and survival of larvae. The model was based on extensive data from local field studies and experiments. With consistently good survival in the pond stages, the simulated population required survival probabilities in the upland stages (juveniles and adults) near 0.5/year to persist and near 0.8/year to achieve the increases observed. Catastrophic failure, occurring randomly with probability 0.5/year, created additional fluctuations in the population, raised the thresholds of survival required for persistence, and caused extinction under conditions that were otherwise favorable. The marbled salamander at Rainbow Bay is not at great risk of extinction because of catastrophic failure, but the risk increases dramatically if life span is decreased or frequency of failure is increased. Any reduction in terrestrial survival will have deleterious consequences by reducing the breeding populations at equilibrium, even if it does not jeopardize persistence. Our model provides assessments of risk that can be applied to poorly studied species with similar life histories, such as the endangered flatwoods salamander ( A. cingulatum ).     

Population viability and harvest sustainability for Madagascar lemurs

Subsistence hunting presents a conservation challenge by which biodiversity preservation must be balanced with safeguarding of human livelihoods. Globally, subsistence hunting threatens primate populations, including Madagascar's endemic lemurs. We used population viability analysis to assess the sustainability of lemur hunting in Makira Natural Park, Madagascar. We identified trends in seasonal hunting of 11 Makira lemur species from household interview data, estimated local lemur densities in populations adjacent to focal villages via transect surveys, and quantified extinction vulnerability for these populations based on species-specific demographic parameters and empirically derived hunting rates. We compared stage-based Lefkovitch with periodic Leslie matrices to evaluate the impact of regional dispersal on persistence trajectories and explored the consequences of perturbations to the timing of peak hunting relative to the lemur birth pulse, under assumptions of density-dependent reproductive compensation. Lemur hunting peaked during the fruit-abundant wet season (March–June). Estimated local lemur densities were roughly inverse to body size across our study area. Life-history modeling indicated that hunting most severely threatened the species with the largest bodies (i.e., Hapalemur occidentalis, Avahi laniger, Daubentonia madagascariensis, and Indri indi), characterized by late-age reproductive onsets and long interbirth intervals. In model simulations, lemur dispersal within a regional metapopulation buffered extinction threats when a majority of local sites supported growth rates above the replacement level but drove regional extirpations when most local sites were overharvested. Hunt simulations were most detrimental when timed to overlap lemur births (a reality for D. madagascariensis and I. indri). In sum, Makira lemurs were overharvested. Regional extirpations, which may contribute to broad-scale extinctions, will be likely if current hunting rates persist. Cessation of anthropogenic lemur harvest is a conservation priority, and development programs are needed to help communities switch from wildlife consumption to domestic protein alternatives.     

Synergistic influences of phase, density, and climatic variation on the dynamics of fluctuating populations

Although ecologists have long recognized that certain mammalian species exhibit high-amplitude, often multiannual, fluctuations in abundance, their causes have remained poorly understood and the subject of intense debate. A key contention has been the relative role of density-dependent and density-independent processes in governing population dynamics. We applied capture-mark-recapture analysis to 25 years of monthly trapping data from a fluctuating prairie vole Microtus ochrogaster population in Illinois, USA, to estimate realized population growth rates and associated vital rates (survival and recruitment) and modeled them as a function of vole density and density-independent climatic variation. We also tested for phase dependence and seasonality in the effects of the above processes. Variation in the realized population growth rate was best explained by phase-specific changes in vole density lagged by one month and mean monthly temperatures with no time lags. The underlying vital rates, survival and recruitment, were influenced by the additive and interactive effects of phase, vole density, and mean monthly temperatures. Our results are consistent with the observation that large-scale population fluctuations are characterized by phase-specific changes in demographic and physiological characteristics. Our findings also support the growing realization that the interaction between climatic variables and density-dependent factors may be a widespread phenomenon, and they suggest that the direction and magnitude of such interactive effects may be phase specific. We conclude that density-dependent and density-independent climatic variables work in tandem during each phase of density fluctuations to drive the dynamics of fluctuating populations.     

Extinction times in experimental populations

Predicting population extinctions is a key element of quantitative conservation biology and population ecology. Although stochastic population theories have long been used to obtain theoretical distributions of population extinction times, model-based predictions have rarely been tested. Here I report results from a quantitative analysis of extinction time in 281 experimental populations of water fleas (Daphnia magna) in variable environments. To my knowledge, this is the first quantitative estimate of the shape of the distribution of population extinction times based on extinction data for any species. The finding that the distribution of population extinction times was extraordinarily peaked is consistent with theoretical predictions for density-independent populations, but inconsistent with predictions for density-dependent populations. The tail of the extinction time distribution was not exponential. These results imply that our current theories of extinction are inadequate. Future work should focus on how demographic stochasticity scales with population size and effects of nonrandom variable environments on population growth and decline.     

Risk spreading, connectivity, and optimal reserve spacing

Two important processes determining the dynamics of spatially structured populations are dispersal and the spatial covariance of demographic fluctuations. Spatially explicit approaches to conservation, such as reserve networks, must consider the tension between these two processes and reach a balance between distances near enough to maintain connectivity, but far enough to benefit from risk spreading. Here, we model this trade-off. We show how two measures of metapopulation persistence depend on the shape of the dispersal kernel and the shape of the distance decay in demographic covariance, and we consider the implications of this trade-off for reserve spacing. The relative rates of distance decay in dispersal and demographic covariance determine whether the long-run metapopulation growth rate, and quasi-extinction risk, peak for adjacent patches or intermediately spaced patches; two local maxima in metapopulation persistence are also possible. When dispersal itself fluctuates over time, the trade-off changes. Temporal variation in mean distance that propagules are dispersed (i.e., propagule advection) decreases metapopulation persistence and decreases the likelihood that persistence will peak for adjacent patches. Conversely, variation in diffusion (the extent of random spread around mean dispersal) increases metapopulation persistence overall and causes it to peak at shorter inter-patch distances. Thus, failure to consider temporal variation in dispersal processes increases the risk that reserve spacings will fail to meet the objective of ensuring metapopulation persistence. This study identifies two phenomena that receive relatively little attention in empirical work on reserve spacing, but that can qualitatively change the effectiveness of reserve spacing strategies: (1) the functional form of the distance decay in covariance among patch-specific demographic rates and (2) temporal variation in the shape of the dispersal kernel. The sensitivity of metapopulation recovery and persistence to how covariance of vital rates decreases with distance suggests that estimating the shape of this function is likely to be as important for effective reserve design as estimating connectivity. Similarly, because temporal variation in dispersal dynamics influences the effect of reserve spacing, approaches to reserve design that ignore such variation, and rely instead on long-term average dispersal patterns, are likely to lead to lower metapopulation viability than is actually achievable.